Ryan McKenna has recently won fourth place and a $3,000 prize in the National Institute of Standards and Technology’s (NIST) second match in the Differential Privacy Synthetic Data Challenge. The competition tests participants’ ability to identify and develop practical methods for creating differentially private synthetic data sets. The challenges include […]

The National Institute of Standards and Technology’s (NIST) Public Safety Communications Research (PSCR) Division is proud to announce the winners of the first of three matches in the Differential Privacy Synthetic Data Challenge. This initiative is the first of its kind in differential privacy and offers a unique opportunity to […]

Ryan McKenna’s paper “Optimizing error of high-dimensional statistical queries under differential privacy” was accepted to VLDB 2018. Xiaolan Wang’s paper “Scalable Semantic Querying of Text” was accepted to VLDB 2018. Authors: Xiaolan Wang, Aaron Feng, Behzad Golshan, Alon Halevy, George Mihaila, Hidekazu Oiwa, Wang-Chiew Tan.